It’s a highly debated question with quantitative data to support all sides. Are 5 point, 7 point, or 9 point scales better suited for generating quality data? Sure, the distribution of responses is slightly different in each case and your ability to conduct more complex statistical analyses can be improved. But I have a few very basic arguments all of which lead me to support scales with fewer items.
- Scales with more points create differences where differences do not exist. Sure, I understand. You want to measure tiny differences. But do consumers REALLY see the difference between 5 and 6 on your 9 point scale? When it comes most ordinary products for most ordinary people, the answer is probably no. Soap is soap and butter is butter and only the brand manager sees the difference.
- Let’s assume, however, that people DO see the difference between 5 and 6 because people take the utmost interest in every product that ever existed. And let’s assume you’ve prepared an extremely comprehensive survey with a multitude of grids measuring a multitude of dimensions. What’s better – 50 grid items using 5 point scales or 50 grid items using 9 point scales. Those 9 point scales are creating nearly twice as much respondent fatigue and an entire group of people is now even less likely to answer the next survey you so carefully prepared.
- How does your analysis plan incorporate those extra scale points? Are you going to provide an average score and standard deviation? If that’s the case, then tell me, how is 3 out of 5 any different than 6 out of 10? I’ll tell you. It’s not. All you’ve done is given yourself a bigger number to work with. And chances are your analysis is incorporating extra error simply because of extra responder fatigue and a higher drop-out rate.
It’s quite simple. Stick with 5 point scales. You’ll generate just as many data points with lots of variability and your survey responders will thank you for it.
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